Application and Research on Weighted Bloom Filter and Bloom Filter in Web Cache

A Bloom filter is a simple space-efficient randomized data structure for representing a set in order to support membership queries. Bloom filters and their generalizations, weighted Bloom filters and compressed Bloom filters have been suggested as a means for sharing web cache information. In this paper, a summary about the current research and application on Bloom filter is first given, and then a comparison of theory and practice between the Bloom filter and weighted Bloom filter is given. In theory, it was proved that weighted Bloom filter has lower false prediction than Bloom filter. But the simulation results showed that Bloom filter is better than weighted. The reason is that weighted Bloom filter needs the necessary conditions, which cannot be satisfied in real world.